Semantic Entity Retrieval Toolkit
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EXPERT_FINDING.md
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README.md
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requirements.txt

README.md

Semantic Entity Retrieval Toolkit

The Semantic Entity Retrieval Toolkit (SERT) is a collection of neural entity retrieval algorithms.

Currently, it hosts an implementation of the following models:

Prerequisites

SERT requires Python 3.5 and assorted modules. The trec_eval utility is required for evaluation and the end-to-end scripts. If you wish to train your models on GPGPUs, you will need a GPU compatible with Theano.

Getting started

To begin, create a virtual Python environment and install dependencies:

[cvangysel@ilps cvangysel] git clone git@github.com:cvangysel/SERT.git
[cvangysel@ilps cvangysel] cd SERT

[cvangysel@ilps SERT] virtualenv SERT-dev
Using base prefix '/Users/cvangysel/anaconda3'
New python executable in /home/cvangysel/SERT/SERT-dev/bin/python
Installing setuptools, pip, wheel...done.

[cvangysel@ilps SERT] source SERT-dev/bin/activate

(SERT-dev) [cvangysel@ilps SERT] pip install -r requirements.txt

Afterwards, follow the examples for expertise retrieval or product search.

Citation

If you use SERT to produce results for your scientific publication, please refer to our WWW 2016 or CIKM 2016 papers:

@inproceedings{VanGysel2016experts,
  title={Unsupervised, Efficient and Semantic Expertise Retrieval},
  author={Van Gysel, Christophe and de Rijke, Maarten and Worring, Marcel},
  booktitle={WWW},
  volume={2016},
  pages={1069--1079},
  year={2016},
  organization={The International World Wide Web Conferences Steering Committee}
}

@inproceedings{VanGysel2016products,
  title={Learning Latent Vector Spaces for Product Search},
  author={Van Gysel, Christophe and de Rijke, Maarten and Kanoulas, Evangelos},
  booktitle={CIKM},
  volume={2016},
  year={2016},
  organization={ACM}
}

License

SERT is licensed under the MIT license. If you modify SERT in any way, please link back to this repository.